Network Model and Optimization of Medical Waste Reverse Logistics by Improved Genetic Algorithm

The medical waste management is of great importance because of the potential environmental hazards and public health risks. Manufacturers have to collect the medical waste and control its recovery or disposal. Medical waste recovery, which encompasses reusing, remanufacturing and materials recycling, requires a specially structured reverse logistics network in order to collect the medical waste efficiently. This paper presents a Mixed Integer Linear Programming model with minimizing costs for medical waste reverse logistics networks. The total costs for reverse logistics include transportation cost, fixed cost of opening the collecting centers and processing centers and operation cost at these facilities over finite planning horizons. An improved genetic algorithm method with a hybrid encoding rule is used to solve the proposed model. The efficiency and practicability of the proposed model is validated by an application to an illustrative example dealing with medical waste returned from some hospitals to a given manufacture.